This repository contains Python code for text preprocessing and manipulation, including auto-correction functionalities using dynamic programming inspired by minimum edit distance. The implemented tasks are outlined as follows:

• Reads a corpus (text file).
• Converts the corpus to lowercase.
• Returns a list of words.

• Returns a dictionary where keys are words, and values are their frequency in the corpus.

• Calculates the probability of each word appearing when randomly selected from the corpus using the formula: P(wi) = C(wi) / M, where C(wi) is the count of word wi and M is the total number of words.

• delete_letter function: Returns all possible strings with one character removed from a given word.
• replace_letter function: Returns all possible strings with one character replaced by another different letter.
• insert_letter function: Returns all possible strings with an additional character inserted into a given word.

• edit_one_letter function: Generates all possible edits one edit away from a word using delete, replace, and insert operations.
• edit_two_letters function: Generates a set of words that are two edits away from a given word using combinations of edit_one_letter function.
• get_corrections function: Provides spelling suggestions based on minimum edit distance logic, prioritizing words with fewer edits.

• Computes the minimum number of edits required to convert one string into another.
• Utilizes a table to efficiently calculate edit distances for substrings of source and target strings.

To effectively use this repository:

1. Clone the Repository:

git clone https://github.com/abrehan2/Autocorrect-Nlp.git